Municipality-level residential technology adoption, energy demand, and CO2 emission in Japan

Description

This page contains data used in the paper shown below. To use the data, please read and cite the paper. Yohei Yamaguchi, Yuanmeng Li, Hideaki Takenaka, Hideaki Uchida, Yoshiyuki Shimoda. Local carbon dioxide emissions: spatially resolved synthetic modelling of technology adoption and building energy demand, Under review. The files contained in the zip file are as follows: 1) AdoptionProb_ALL_Elec.csv: Adoption probability of all-electric option in municipalities. 2) AdoptionProb_CK.csv: Adoption probability of cooking stove fuel types. “Gas”, “IH”, and “Electric” indicate gas stoves, IH cooking heaters, and electric cooking heaters. 3) AdoptionProb_WH.csv: Adoption probability of water heating system types. “Electric”, “HP”, “Gas”, “Kerosene”, and “CGS” indicate electric water heaters, air-source heat pumps, gas heaters, kerosene heaters, and cogeneration systems. “Non” indicates the proportion of households without a water heater. 4) AdoptionProb_SH.csv: Adoption probability of space heating system types. “Electric”, “HP”, “Gas”, “Kerosene”, and “Bio” indicate electric heaters, air-source heat pumps, gas heaters, kerosene heaters, and biomass heaters. “Non” indicates the proportion of households without a space heating system. 5) AdoptionProb_FloorHT.csv: Adoption probability of floor heating system. 6) Energy_EstimatedBySARmodel.csv: Energy consumption (in primary energy) estimated by the SAR (spatial autoregressive) model. “Electricity”, “CityGas”, “LPG”, “Kerosene”, and “Total” indicates electricity, city gas, LPG, kerosene, and total primary energy consumption. “CO2_Total” indicates the total CO2 emission. 7) Energy_EstimatedBySARmodel.csv: Energy consumption (in primary energy) estimated for 2019 by the synthetic BSEM (building stock energy model) proposed in the paper. “Electricity”, “Gas”, “Kerosene”, and “Total” indicate electricity, gas, kerosene, and total primary energy consumptions. “CO2_Total”, “Direct_CO2”, “Indirect_CO2” indicate the total, direct, and indirect CO2 emissions. 8) Energy_EstimatedBySARmodel.csv: Energy consumption (in primary energy) estimated for 2050 by the synthetic BSEM (building stock energy model) proposed in the paper. “Electricity”, “Gas”, and “Kerosene” indicate electricity, gas, and kerosene. The result also contains those estimated for the year 2019. The first column of all the files contains the municipality codes, a five-digit code given to Japanese municipalities as defined in JIS X 0402. The other columns contain the data listed above. The column name uses "Obs_" and "Est_" to indicate the distinction between observation and estimation data.

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The procedure is explained in the paper.

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